{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Riskfolio-Lib Tutorial: \n",
    "<br>__[Financionerioncios](https://financioneroncios.wordpress.com)__\n",
    "<br>__[Orenji](https://www.orenj-i.net)__\n",
    "<br>__[Riskfolio-Lib](https://riskfolio-lib.readthedocs.io/en/latest/)__\n",
    "<br>__[Dany Cajas](https://www.linkedin.com/in/dany-cajas/)__\n",
    "<a href='https://ko-fi.com/B0B833SXD' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://cdn.ko-fi.com/cdn/kofi1.png?v=2' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a> \n",
    "\n",
    "## Tutorial 1: Classic Mean Risk Optimization\n",
    "\n",
    "## 1. Downloading the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  25 of 25 completed\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "yf.pdr_override()\n",
    "pd.options.display.float_format = '{:.4%}'.format\n",
    "\n",
    "# Date range\n",
    "start = '2016-01-01'\n",
    "end = '2019-12-30'\n",
    "\n",
    "# Tickers of assets\n",
    "assets = ['JCI', 'TGT', 'CMCSA', 'CPB', 'MO', 'APA', 'MMC', 'JPM',\n",
    "          'ZION', 'PSA', 'BAX', 'BMY', 'LUV', 'PCAR', 'TXT', 'TMO',\n",
    "          'DE', 'MSFT', 'HPQ', 'SEE', 'VZ', 'CNP', 'NI', 'T', 'BA']\n",
    "assets.sort()\n",
    "\n",
    "# Downloading data\n",
    "data = yf.download(assets, start = start, end = end)\n",
    "data = data.loc[:,('Adj Close', slice(None))]\n",
    "data.columns = assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>-2.0257%</td>\n",
       "      <td>0.4057%</td>\n",
       "      <td>0.4036%</td>\n",
       "      <td>1.9693%</td>\n",
       "      <td>0.0180%</td>\n",
       "      <td>0.9305%</td>\n",
       "      <td>0.3678%</td>\n",
       "      <td>0.5783%</td>\n",
       "      <td>0.9483%</td>\n",
       "      <td>-1.1953%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.5881%</td>\n",
       "      <td>0.0212%</td>\n",
       "      <td>2.8236%</td>\n",
       "      <td>0.9758%</td>\n",
       "      <td>0.6987%</td>\n",
       "      <td>1.7539%</td>\n",
       "      <td>-0.1730%</td>\n",
       "      <td>0.2409%</td>\n",
       "      <td>1.3735%</td>\n",
       "      <td>-1.0857%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-06</th>\n",
       "      <td>-11.4863%</td>\n",
       "      <td>-1.5879%</td>\n",
       "      <td>0.2411%</td>\n",
       "      <td>-1.7557%</td>\n",
       "      <td>-0.7727%</td>\n",
       "      <td>-1.2473%</td>\n",
       "      <td>-0.1736%</td>\n",
       "      <td>-1.1239%</td>\n",
       "      <td>-3.5867%</td>\n",
       "      <td>-0.9551%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5547%</td>\n",
       "      <td>0.0212%</td>\n",
       "      <td>0.1592%</td>\n",
       "      <td>-1.5647%</td>\n",
       "      <td>-0.1466%</td>\n",
       "      <td>-1.0155%</td>\n",
       "      <td>-0.7653%</td>\n",
       "      <td>-3.0048%</td>\n",
       "      <td>-0.9035%</td>\n",
       "      <td>-2.9145%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-07</th>\n",
       "      <td>-5.1389%</td>\n",
       "      <td>-4.1922%</td>\n",
       "      <td>-1.6573%</td>\n",
       "      <td>-2.7699%</td>\n",
       "      <td>-1.1047%</td>\n",
       "      <td>-1.9769%</td>\n",
       "      <td>-1.2207%</td>\n",
       "      <td>-0.8855%</td>\n",
       "      <td>-4.6059%</td>\n",
       "      <td>-2.5394%</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.2066%</td>\n",
       "      <td>-3.0309%</td>\n",
       "      <td>-1.0411%</td>\n",
       "      <td>-3.1557%</td>\n",
       "      <td>-1.6148%</td>\n",
       "      <td>-0.2700%</td>\n",
       "      <td>-2.2845%</td>\n",
       "      <td>-2.0570%</td>\n",
       "      <td>-0.5492%</td>\n",
       "      <td>-3.0019%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-08</th>\n",
       "      <td>0.2737%</td>\n",
       "      <td>-2.2705%</td>\n",
       "      <td>-1.6037%</td>\n",
       "      <td>-2.5425%</td>\n",
       "      <td>0.1099%</td>\n",
       "      <td>-0.2241%</td>\n",
       "      <td>0.5706%</td>\n",
       "      <td>-1.6402%</td>\n",
       "      <td>-1.7641%</td>\n",
       "      <td>-0.1649%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1539%</td>\n",
       "      <td>-1.1366%</td>\n",
       "      <td>-0.7308%</td>\n",
       "      <td>-0.1448%</td>\n",
       "      <td>0.0895%</td>\n",
       "      <td>-3.3839%</td>\n",
       "      <td>-0.1117%</td>\n",
       "      <td>-1.1387%</td>\n",
       "      <td>-0.9719%</td>\n",
       "      <td>-1.1254%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11</th>\n",
       "      <td>-4.3384%</td>\n",
       "      <td>0.1693%</td>\n",
       "      <td>-1.6851%</td>\n",
       "      <td>-1.0215%</td>\n",
       "      <td>0.0915%</td>\n",
       "      <td>-1.1791%</td>\n",
       "      <td>0.5674%</td>\n",
       "      <td>0.5287%</td>\n",
       "      <td>0.6616%</td>\n",
       "      <td>0.0331%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6436%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.9869%</td>\n",
       "      <td>-0.1450%</td>\n",
       "      <td>1.2224%</td>\n",
       "      <td>1.4570%</td>\n",
       "      <td>0.5367%</td>\n",
       "      <td>-0.4607%</td>\n",
       "      <td>0.5800%</td>\n",
       "      <td>-1.9919%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 APA       BA      BAX      BMY    CMCSA      CNP      CPB  \\\n",
       "Date                                                                         \n",
       "2016-01-05  -2.0257%  0.4057%  0.4036%  1.9693%  0.0180%  0.9305%  0.3678%   \n",
       "2016-01-06 -11.4863% -1.5879%  0.2411% -1.7557% -0.7727% -1.2473% -0.1736%   \n",
       "2016-01-07  -5.1389% -4.1922% -1.6573% -2.7699% -1.1047% -1.9769% -1.2207%   \n",
       "2016-01-08   0.2737% -2.2705% -1.6037% -2.5425%  0.1099% -0.2241%  0.5706%   \n",
       "2016-01-11  -4.3384%  0.1693% -1.6851% -1.0215%  0.0915% -1.1791%  0.5674%   \n",
       "\n",
       "                 DE      HPQ      JCI  ...       NI     PCAR      PSA  \\\n",
       "Date                                   ...                              \n",
       "2016-01-05  0.5783%  0.9483% -1.1953%  ...  1.5881%  0.0212%  2.8236%   \n",
       "2016-01-06 -1.1239% -3.5867% -0.9551%  ...  0.5547%  0.0212%  0.1592%   \n",
       "2016-01-07 -0.8855% -4.6059% -2.5394%  ... -2.2066% -3.0309% -1.0411%   \n",
       "2016-01-08 -1.6402% -1.7641% -0.1649%  ... -0.1539% -1.1366% -0.7308%   \n",
       "2016-01-11  0.5287%  0.6616%  0.0331%  ...  1.6436%  0.0000%  0.9869%   \n",
       "\n",
       "                SEE        T      TGT      TMO      TXT       VZ     ZION  \n",
       "Date                                                                       \n",
       "2016-01-05  0.9758%  0.6987%  1.7539% -0.1730%  0.2409%  1.3735% -1.0857%  \n",
       "2016-01-06 -1.5647% -0.1466% -1.0155% -0.7653% -3.0048% -0.9035% -2.9145%  \n",
       "2016-01-07 -3.1557% -1.6148% -0.2700% -2.2845% -2.0570% -0.5492% -3.0019%  \n",
       "2016-01-08 -0.1448%  0.0895% -3.3839% -0.1117% -1.1387% -0.9719% -1.1254%  \n",
       "2016-01-11 -0.1450%  1.2224%  1.4570%  0.5367% -0.4607%  0.5800% -1.9919%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculating returns\n",
    "\n",
    "Y = data[assets].pct_change().dropna()\n",
    "\n",
    "display(Y.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Estimating Mean Variance Portfolios\n",
    "\n",
    "### 2.1 Calculating the portfolio that maximizes Sharpe ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.1589%</td>\n",
       "      <td>11.5018%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>8.4807%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.8194%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>10.8263%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.1805%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.2740%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA      BAX     BMY   CMCSA     CNP     CPB      DE  \\\n",
       "weights 0.0000% 6.1589% 11.5018% 0.0000% 0.0000% 8.4807% 0.0000% 3.8194%   \n",
       "\n",
       "            HPQ     JCI  ...       NI    PCAR     PSA     SEE       T     TGT  \\\n",
       "weights 0.0000% 0.0000%  ... 10.8263% 0.0000% 0.0000% 0.0000% 0.0000% 7.1805%   \n",
       "\n",
       "            TMO     TXT      VZ    ZION  \n",
       "weights 0.0000% 0.0000% 4.2740% 0.0000%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import riskfolio.Portfolio as pf\n",
    "\n",
    "# Building the portfolio object\n",
    "port = pf.Portfolio(returns=Y)\n",
    "# Calculating optimum portfolio\n",
    "\n",
    "# Select method and estimate input parameters:\n",
    "\n",
    "method_mu='hist' # Method to estimate expected returns based on historical data.\n",
    "method_cov='hist' # Method to estimate covariance matrix based on historical data.\n",
    "\n",
    "port.assets_stats(method_mu=method_mu, method_cov=method_cov, d=0.94)\n",
    "\n",
    "# Estimate optimal portfolio:\n",
    "\n",
    "model='Classic' # Could be Classic (historical), BL (Black Litterman) or FM (Factor Model)\n",
    "rm = 'MV' # Risk measure used, this time will be variance\n",
    "obj = 'Sharpe' # Objective function, could be MinRisk, MaxRet, Utility or Sharpe\n",
    "hist = True # Use historical scenarios for risk measures that depend on scenarios\n",
    "rf = 0 # Risk free rate\n",
    "l = 0 # Risk aversion factor, only useful when obj is 'Utility'\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import riskfolio.PlotFunctions as plf\n",
    "\n",
    "# Plotting the composition of the portfolio\n",
    "\n",
    "ax = plf.plot_pie(w=w, title='Sharpe Mean Variance', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                  height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Calculate efficient frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.2634%</td>\n",
       "      <td>4.3887%</td>\n",
       "      <td>2.1705%</td>\n",
       "      <td>6.9871%</td>\n",
       "      <td>3.2390%</td>\n",
       "      <td>0.0787%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.8376%</td>\n",
       "      <td>...</td>\n",
       "      <td>11.4509%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>14.9184%</td>\n",
       "      <td>0.1629%</td>\n",
       "      <td>6.4196%</td>\n",
       "      <td>4.0904%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>8.3447%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.0325%</td>\n",
       "      <td>8.4717%</td>\n",
       "      <td>0.8579%</td>\n",
       "      <td>1.9327%</td>\n",
       "      <td>8.5940%</td>\n",
       "      <td>2.1946%</td>\n",
       "      <td>1.4377%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.1060%</td>\n",
       "      <td>...</td>\n",
       "      <td>13.4410%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.2131%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.1682%</td>\n",
       "      <td>5.5286%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.4731%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.8407%</td>\n",
       "      <td>9.3406%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.5588%</td>\n",
       "      <td>9.1990%</td>\n",
       "      <td>1.7699%</td>\n",
       "      <td>1.8516%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.2108%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.2140%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.5518%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.1593%</td>\n",
       "      <td>6.0609%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.9971%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.4596%</td>\n",
       "      <td>9.8935%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.0707%</td>\n",
       "      <td>9.6311%</td>\n",
       "      <td>1.2503%</td>\n",
       "      <td>2.0912%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.7830%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.9064%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.9202%</td>\n",
       "      <td>6.4433%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.5067%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.9674%</td>\n",
       "      <td>10.3313%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.5839%</td>\n",
       "      <td>9.9784%</td>\n",
       "      <td>0.6012%</td>\n",
       "      <td>2.2744%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>15.1469%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.3826%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.5557%</td>\n",
       "      <td>6.7335%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.8300%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      APA      BA      BAX     BMY   CMCSA     CNP     CPB      DE     HPQ  \\\n",
       "0 0.0000% 0.0000%  5.2634% 4.3887% 2.1705% 6.9871% 3.2390% 0.0787% 0.0000%   \n",
       "1 0.0000% 2.0325%  8.4717% 0.8579% 1.9327% 8.5940% 2.1946% 1.4377% 0.0000%   \n",
       "2 0.0000% 2.8407%  9.3406% 0.0000% 1.5588% 9.1990% 1.7699% 1.8516% 0.0000%   \n",
       "3 0.0000% 3.4596%  9.8935% 0.0000% 1.0707% 9.6311% 1.2503% 2.0912% 0.0000%   \n",
       "4 0.0000% 3.9674% 10.3313% 0.0000% 0.5839% 9.9784% 0.6012% 2.2744% 0.0000%   \n",
       "\n",
       "      JCI  ...       NI    PCAR      PSA     SEE       T     TGT     TMO  \\\n",
       "0 2.8376%  ... 11.4509% 0.0000% 14.9184% 0.1629% 6.4196% 4.0904% 0.0000%   \n",
       "1 1.1060%  ... 13.4410% 0.0000%  9.2131% 0.0000% 4.1682% 5.5286% 0.0000%   \n",
       "2 0.2108%  ... 14.2140% 0.0000%  6.5518% 0.0000% 3.1593% 6.0609% 0.0000%   \n",
       "3 0.0000%  ... 14.7830% 0.0000%  3.9064% 0.0000% 1.9202% 6.4433% 0.0000%   \n",
       "4 0.0000%  ... 15.1469% 0.0000%  1.3826% 0.0000% 0.5557% 6.7335% 0.0000%   \n",
       "\n",
       "      TXT       VZ    ZION  \n",
       "0 0.0000%  8.3447% 0.0000%  \n",
       "1 0.0000%  9.4731% 0.0000%  \n",
       "2 0.0000%  9.9971% 0.0000%  \n",
       "3 0.0000% 10.5067% 0.0000%  \n",
       "4 0.0000% 10.8300% 0.0000%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points = 50 # Number of points of the frontier\n",
    "\n",
    "frontier = port.efficient_frontier(model=model, rm=rm, points=points, rf=rf, hist=hist)\n",
    "\n",
    "display(frontier.T.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the efficient frontier\n",
    "\n",
    "label = 'Max Risk Adjusted Return Portfolio' # Title of point\n",
    "mu = port.mu # Expected returns\n",
    "cov = port.cov # Covariance matrix\n",
    "returns = port.returns # Returns of the assets\n",
    "\n",
    "ax = plf.plot_frontier(w_frontier=frontier, mu=mu, cov=cov, returns=returns, rm=rm,\n",
    "                       rf=rf, alpha=0.05, cmap='viridis', w=w, label=label,\n",
    "                       marker='*', s=16, c='r', height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = plf.plot_frontier_area(w_frontier=frontier, cmap=\"tab20\", height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Estimating Mean Risk Portfolios\n",
    "\n",
    "In this part I will calculate optimal portfolios for several risk measures. First I'm going to calculate the portfolio that maximizes risk adjusted return when CVaR is the risk measure, then I'm going to calculate the portfolios that maximize the risk adjusted return for all available risk measures.\n",
    "\n",
    "### 3.1 Calculating the portfolio that maximizes Return/CVaR ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>12.3495%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.4900%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.1436%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>12.6860%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.1967%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.6768%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA      BAX     BMY   CMCSA     CNP     CPB      DE  \\\n",
       "weights 0.0000% 0.0000% 12.3495% 0.0000% 0.0000% 7.4900% 0.0000% 5.1436%   \n",
       "\n",
       "            HPQ     JCI  ...       NI    PCAR     PSA     SEE       T  \\\n",
       "weights 0.0000% 0.0000%  ... 12.6860% 0.0000% 0.0000% 0.0000% 0.0000%   \n",
       "\n",
       "             TGT     TMO     TXT      VZ    ZION  \n",
       "weights 11.1967% 0.0000% 0.0000% 3.6768% 0.0000%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rm = 'CVaR' # Risk measure\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plf.plot_pie(w=w, title='Sharpe Mean CVaR', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                  height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 Calculate efficient frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.0453%</td>\n",
       "      <td>7.0613%</td>\n",
       "      <td>0.2201%</td>\n",
       "      <td>2.1293%</td>\n",
       "      <td>8.0717%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.8042%</td>\n",
       "      <td>...</td>\n",
       "      <td>6.9252%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>21.0638%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.6449%</td>\n",
       "      <td>4.1220%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>20.7628%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.4071%</td>\n",
       "      <td>5.6730%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.2091%</td>\n",
       "      <td>4.8807%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.7991%</td>\n",
       "      <td>...</td>\n",
       "      <td>7.7321%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>14.6331%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.3233%</td>\n",
       "      <td>7.1050%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>19.9767%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.0123%</td>\n",
       "      <td>3.6373%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.6362%</td>\n",
       "      <td>0.3457%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.0866%</td>\n",
       "      <td>...</td>\n",
       "      <td>7.1911%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.7316%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.7583%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>19.3524%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.8331%</td>\n",
       "      <td>0.1434%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>12.8628%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.6486%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.4083%</td>\n",
       "      <td>...</td>\n",
       "      <td>7.4419%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.4669%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>8.2885%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>17.5778%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.7507%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>13.4656%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.7690%</td>\n",
       "      <td>...</td>\n",
       "      <td>8.4720%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.2948%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.5457%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>14.2040%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      APA      BA     BAX     BMY   CMCSA      CNP     CPB      DE     HPQ  \\\n",
       "0 0.0000% 0.0000% 2.0453% 7.0613% 0.2201%  2.1293% 8.0717% 0.0000% 0.0000%   \n",
       "1 0.0000% 0.0000% 4.4071% 5.6730% 0.0000%  6.2091% 4.8807% 0.0000% 0.0000%   \n",
       "2 0.0000% 0.0000% 6.0123% 3.6373% 0.0000% 11.6362% 0.3457% 0.0000% 0.0000%   \n",
       "3 0.0000% 0.0000% 6.8331% 0.1434% 0.0000% 12.8628% 0.0000% 0.6486% 0.0000%   \n",
       "4 0.0000% 0.0000% 7.7507% 0.0000% 0.0000% 13.4656% 0.0000% 0.0000% 0.0000%   \n",
       "\n",
       "      JCI  ...      NI    PCAR      PSA     SEE       T      TGT     TMO  \\\n",
       "0 3.8042%  ... 6.9252% 0.0000% 21.0638% 0.0000% 2.6449%  4.1220% 0.0000%   \n",
       "1 1.7991%  ... 7.7321% 0.0000% 14.6331% 0.0000% 1.3233%  7.1050% 0.0000%   \n",
       "2 3.0866%  ... 7.1911% 0.0000% 11.7316% 0.0000% 0.0000%  6.7583% 0.0000%   \n",
       "3 0.4083%  ... 7.4419% 0.0000% 10.4669% 0.0000% 0.0000%  8.2885% 0.0000%   \n",
       "4 0.7690%  ... 8.4720% 0.0000%  5.2948% 0.0000% 0.0000% 10.5457% 0.0000%   \n",
       "\n",
       "      TXT       VZ    ZION  \n",
       "0 0.0000% 20.7628% 0.0000%  \n",
       "1 0.0000% 19.9767% 0.0000%  \n",
       "2 0.0000% 19.3524% 0.0000%  \n",
       "3 0.0000% 17.5778% 0.0000%  \n",
       "4 0.0000% 14.2040% 0.0000%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points = 50 # Number of points of the frontier\n",
    "\n",
    "frontier = port.efficient_frontier(model=model, rm=rm, points=points, rf=rf, hist=hist)\n",
    "\n",
    "display(frontier.T.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "label = 'Max Risk Adjusted Return Portfolio' # Title of point\n",
    "\n",
    "ax = plf.plot_frontier(w_frontier=frontier, mu=mu, cov=cov, returns=returns, rm=rm,\n",
    "                       rf=rf, alpha=0.05, cmap='viridis', w=w, label=label,\n",
    "                       marker='*', s=16, c='r', height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = plf.plot_frontier_area(w_frontier=frontier, cmap=\"tab20\", height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.4 Calculate Optimal Portfolios for Several Risk Measures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Risk Measures available:\n",
    "#\n",
    "# 'MV': Standard Deviation.\n",
    "# 'MAD': Mean Absolute Deviation.\n",
    "# 'MSV': Semi Standard Deviation.\n",
    "# 'FLPM': First Lower Partial Moment (Omega Ratio).\n",
    "# 'SLPM': Second Lower Partial Moment (Sortino Ratio).\n",
    "# 'CVaR': Conditional Value at Risk.\n",
    "# 'EVaR': Entropic Value at Risk.\n",
    "# 'WR': Worst Realization (Minimax)\n",
    "# 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).\n",
    "# 'ADD': Average Drawdown of uncompounded cumulative returns.\n",
    "# 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'UCI': Ulcer Index of uncompounded cumulative returns.\n",
    "\n",
    "rms = ['MV', 'MAD', 'MSV', 'FLPM', 'SLPM', 'CVaR',\n",
    "       'EVaR', 'WR', 'MDD', 'ADD', 'CDaR', 'UCI', 'EDaR']\n",
    "\n",
    "w_s = pd.DataFrame([])\n",
    "\n",
    "for i in rms:\n",
    "    w = port.optimization(model=model, rm=i, obj=obj, rf=rf, l=l, hist=hist)\n",
    "    w_s = pd.concat([w_s, w], axis=1)\n",
    "    \n",
    "w_s.columns = rms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        }</style><table id=\"T_0b76b_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >MV</th>        <th class=\"col_heading level0 col1\" >MAD</th>        <th class=\"col_heading level0 col2\" >MSV</th>        <th class=\"col_heading level0 col3\" >FLPM</th>        <th class=\"col_heading level0 col4\" >SLPM</th>        <th class=\"col_heading level0 col5\" >CVaR</th>        <th class=\"col_heading level0 col6\" >EVaR</th>        <th class=\"col_heading level0 col7\" >WR</th>        <th class=\"col_heading level0 col8\" >MDD</th>        <th class=\"col_heading level0 col9\" >ADD</th>        <th class=\"col_heading level0 col10\" >CDaR</th>        <th class=\"col_heading level0 col11\" >UCI</th>        <th class=\"col_heading level0 col12\" >EDaR</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_0b76b_level0_row0\" class=\"row_heading level0 row0\" >APA</th>\n",
       "                        <td id=\"T_0b76b_row0_col0\" class=\"data row0 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col1\" class=\"data row0 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col2\" class=\"data row0 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col3\" class=\"data row0 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col4\" class=\"data row0 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col5\" class=\"data row0 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col6\" class=\"data row0 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col7\" class=\"data row0 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col8\" class=\"data row0 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col9\" class=\"data row0 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col10\" class=\"data row0 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col11\" class=\"data row0 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row0_col12\" class=\"data row0 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row1\" class=\"row_heading level0 row1\" >BA</th>\n",
       "                        <td id=\"T_0b76b_row1_col0\" class=\"data row1 col0\" >6.16%</td>\n",
       "                        <td id=\"T_0b76b_row1_col1\" class=\"data row1 col1\" >7.58%</td>\n",
       "                        <td id=\"T_0b76b_row1_col2\" class=\"data row1 col2\" >4.38%</td>\n",
       "                        <td id=\"T_0b76b_row1_col3\" class=\"data row1 col3\" >6.30%</td>\n",
       "                        <td id=\"T_0b76b_row1_col4\" class=\"data row1 col4\" >3.98%</td>\n",
       "                        <td id=\"T_0b76b_row1_col5\" class=\"data row1 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row1_col6\" class=\"data row1 col6\" >1.55%</td>\n",
       "                        <td id=\"T_0b76b_row1_col7\" class=\"data row1 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row1_col8\" class=\"data row1 col8\" >1.20%</td>\n",
       "                        <td id=\"T_0b76b_row1_col9\" class=\"data row1 col9\" >6.87%</td>\n",
       "                        <td id=\"T_0b76b_row1_col10\" class=\"data row1 col10\" >2.82%</td>\n",
       "                        <td id=\"T_0b76b_row1_col11\" class=\"data row1 col11\" >6.34%</td>\n",
       "                        <td id=\"T_0b76b_row1_col12\" class=\"data row1 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row2\" class=\"row_heading level0 row2\" >BAX</th>\n",
       "                        <td id=\"T_0b76b_row2_col0\" class=\"data row2 col0\" >11.50%</td>\n",
       "                        <td id=\"T_0b76b_row2_col1\" class=\"data row2 col1\" >9.44%</td>\n",
       "                        <td id=\"T_0b76b_row2_col2\" class=\"data row2 col2\" >10.37%</td>\n",
       "                        <td id=\"T_0b76b_row2_col3\" class=\"data row2 col3\" >8.96%</td>\n",
       "                        <td id=\"T_0b76b_row2_col4\" class=\"data row2 col4\" >10.62%</td>\n",
       "                        <td id=\"T_0b76b_row2_col5\" class=\"data row2 col5\" >12.35%</td>\n",
       "                        <td id=\"T_0b76b_row2_col6\" class=\"data row2 col6\" >4.46%</td>\n",
       "                        <td id=\"T_0b76b_row2_col7\" class=\"data row2 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row2_col8\" class=\"data row2 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row2_col9\" class=\"data row2 col9\" >4.71%</td>\n",
       "                        <td id=\"T_0b76b_row2_col10\" class=\"data row2 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row2_col11\" class=\"data row2 col11\" >4.34%</td>\n",
       "                        <td id=\"T_0b76b_row2_col12\" class=\"data row2 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row3\" class=\"row_heading level0 row3\" >BMY</th>\n",
       "                        <td id=\"T_0b76b_row3_col0\" class=\"data row3 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col1\" class=\"data row3 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col2\" class=\"data row3 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col3\" class=\"data row3 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col4\" class=\"data row3 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col5\" class=\"data row3 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col6\" class=\"data row3 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col7\" class=\"data row3 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col8\" class=\"data row3 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col9\" class=\"data row3 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col10\" class=\"data row3 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col11\" class=\"data row3 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row3_col12\" class=\"data row3 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row4\" class=\"row_heading level0 row4\" >CMCSA</th>\n",
       "                        <td id=\"T_0b76b_row4_col0\" class=\"data row4 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col1\" class=\"data row4 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col2\" class=\"data row4 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col3\" class=\"data row4 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col4\" class=\"data row4 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col5\" class=\"data row4 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col6\" class=\"data row4 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col7\" class=\"data row4 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col8\" class=\"data row4 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col9\" class=\"data row4 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col10\" class=\"data row4 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col11\" class=\"data row4 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row4_col12\" class=\"data row4 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row5\" class=\"row_heading level0 row5\" >CNP</th>\n",
       "                        <td id=\"T_0b76b_row5_col0\" class=\"data row5 col0\" >8.48%</td>\n",
       "                        <td id=\"T_0b76b_row5_col1\" class=\"data row5 col1\" >7.25%</td>\n",
       "                        <td id=\"T_0b76b_row5_col2\" class=\"data row5 col2\" >9.15%</td>\n",
       "                        <td id=\"T_0b76b_row5_col3\" class=\"data row5 col3\" >6.00%</td>\n",
       "                        <td id=\"T_0b76b_row5_col4\" class=\"data row5 col4\" >9.38%</td>\n",
       "                        <td id=\"T_0b76b_row5_col5\" class=\"data row5 col5\" >7.49%</td>\n",
       "                        <td id=\"T_0b76b_row5_col6\" class=\"data row5 col6\" >30.26%</td>\n",
       "                        <td id=\"T_0b76b_row5_col7\" class=\"data row5 col7\" >28.96%</td>\n",
       "                        <td id=\"T_0b76b_row5_col8\" class=\"data row5 col8\" >56.01%</td>\n",
       "                        <td id=\"T_0b76b_row5_col9\" class=\"data row5 col9\" >13.71%</td>\n",
       "                        <td id=\"T_0b76b_row5_col10\" class=\"data row5 col10\" >32.93%</td>\n",
       "                        <td id=\"T_0b76b_row5_col11\" class=\"data row5 col11\" >18.16%</td>\n",
       "                        <td id=\"T_0b76b_row5_col12\" class=\"data row5 col12\" >42.52%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row6\" class=\"row_heading level0 row6\" >CPB</th>\n",
       "                        <td id=\"T_0b76b_row6_col0\" class=\"data row6 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col1\" class=\"data row6 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col2\" class=\"data row6 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col3\" class=\"data row6 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col4\" class=\"data row6 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col5\" class=\"data row6 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col6\" class=\"data row6 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col7\" class=\"data row6 col7\" >5.37%</td>\n",
       "                        <td id=\"T_0b76b_row6_col8\" class=\"data row6 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col9\" class=\"data row6 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col10\" class=\"data row6 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col11\" class=\"data row6 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row6_col12\" class=\"data row6 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row7\" class=\"row_heading level0 row7\" >DE</th>\n",
       "                        <td id=\"T_0b76b_row7_col0\" class=\"data row7 col0\" >3.82%</td>\n",
       "                        <td id=\"T_0b76b_row7_col1\" class=\"data row7 col1\" >2.72%</td>\n",
       "                        <td id=\"T_0b76b_row7_col2\" class=\"data row7 col2\" >1.18%</td>\n",
       "                        <td id=\"T_0b76b_row7_col3\" class=\"data row7 col3\" >2.32%</td>\n",
       "                        <td id=\"T_0b76b_row7_col4\" class=\"data row7 col4\" >0.90%</td>\n",
       "                        <td id=\"T_0b76b_row7_col5\" class=\"data row7 col5\" >5.14%</td>\n",
       "                        <td id=\"T_0b76b_row7_col6\" class=\"data row7 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row7_col7\" class=\"data row7 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row7_col8\" class=\"data row7 col8\" >13.08%</td>\n",
       "                        <td id=\"T_0b76b_row7_col9\" class=\"data row7 col9\" >1.55%</td>\n",
       "                        <td id=\"T_0b76b_row7_col10\" class=\"data row7 col10\" >0.82%</td>\n",
       "                        <td id=\"T_0b76b_row7_col11\" class=\"data row7 col11\" >1.01%</td>\n",
       "                        <td id=\"T_0b76b_row7_col12\" class=\"data row7 col12\" >3.21%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row8\" class=\"row_heading level0 row8\" >HPQ</th>\n",
       "                        <td id=\"T_0b76b_row8_col0\" class=\"data row8 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col1\" class=\"data row8 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col2\" class=\"data row8 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col3\" class=\"data row8 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col4\" class=\"data row8 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col5\" class=\"data row8 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col6\" class=\"data row8 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col7\" class=\"data row8 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col8\" class=\"data row8 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col9\" class=\"data row8 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col10\" class=\"data row8 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col11\" class=\"data row8 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row8_col12\" class=\"data row8 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row9\" class=\"row_heading level0 row9\" >JCI</th>\n",
       "                        <td id=\"T_0b76b_row9_col0\" class=\"data row9 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col1\" class=\"data row9 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col2\" class=\"data row9 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col3\" class=\"data row9 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col4\" class=\"data row9 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col5\" class=\"data row9 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col6\" class=\"data row9 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col7\" class=\"data row9 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col8\" class=\"data row9 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col9\" class=\"data row9 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col10\" class=\"data row9 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col11\" class=\"data row9 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row9_col12\" class=\"data row9 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row10\" class=\"row_heading level0 row10\" >JPM</th>\n",
       "                        <td id=\"T_0b76b_row10_col0\" class=\"data row10 col0\" >8.63%</td>\n",
       "                        <td id=\"T_0b76b_row10_col1\" class=\"data row10 col1\" >14.80%</td>\n",
       "                        <td id=\"T_0b76b_row10_col2\" class=\"data row10 col2\" >8.82%</td>\n",
       "                        <td id=\"T_0b76b_row10_col3\" class=\"data row10 col3\" >16.70%</td>\n",
       "                        <td id=\"T_0b76b_row10_col4\" class=\"data row10 col4\" >8.46%</td>\n",
       "                        <td id=\"T_0b76b_row10_col5\" class=\"data row10 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row10_col6\" class=\"data row10 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row10_col7\" class=\"data row10 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row10_col8\" class=\"data row10 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row10_col9\" class=\"data row10 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row10_col10\" class=\"data row10 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row10_col11\" class=\"data row10 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row10_col12\" class=\"data row10 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row11\" class=\"row_heading level0 row11\" >LUV</th>\n",
       "                        <td id=\"T_0b76b_row11_col0\" class=\"data row11 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col1\" class=\"data row11 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col2\" class=\"data row11 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col3\" class=\"data row11 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col4\" class=\"data row11 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col5\" class=\"data row11 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col6\" class=\"data row11 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col7\" class=\"data row11 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col8\" class=\"data row11 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col9\" class=\"data row11 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col10\" class=\"data row11 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col11\" class=\"data row11 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row11_col12\" class=\"data row11 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row12\" class=\"row_heading level0 row12\" >MMC</th>\n",
       "                        <td id=\"T_0b76b_row12_col0\" class=\"data row12 col0\" >21.54%</td>\n",
       "                        <td id=\"T_0b76b_row12_col1\" class=\"data row12 col1\" >14.10%</td>\n",
       "                        <td id=\"T_0b76b_row12_col2\" class=\"data row12 col2\" >21.24%</td>\n",
       "                        <td id=\"T_0b76b_row12_col3\" class=\"data row12 col3\" >14.18%</td>\n",
       "                        <td id=\"T_0b76b_row12_col4\" class=\"data row12 col4\" >21.58%</td>\n",
       "                        <td id=\"T_0b76b_row12_col5\" class=\"data row12 col5\" >28.82%</td>\n",
       "                        <td id=\"T_0b76b_row12_col6\" class=\"data row12 col6\" >15.48%</td>\n",
       "                        <td id=\"T_0b76b_row12_col7\" class=\"data row12 col7\" >31.77%</td>\n",
       "                        <td id=\"T_0b76b_row12_col8\" class=\"data row12 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row12_col9\" class=\"data row12 col9\" >17.66%</td>\n",
       "                        <td id=\"T_0b76b_row12_col10\" class=\"data row12 col10\" >7.46%</td>\n",
       "                        <td id=\"T_0b76b_row12_col11\" class=\"data row12 col11\" >15.14%</td>\n",
       "                        <td id=\"T_0b76b_row12_col12\" class=\"data row12 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row13\" class=\"row_heading level0 row13\" >MO</th>\n",
       "                        <td id=\"T_0b76b_row13_col0\" class=\"data row13 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col1\" class=\"data row13 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col2\" class=\"data row13 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col3\" class=\"data row13 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col4\" class=\"data row13 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col5\" class=\"data row13 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col6\" class=\"data row13 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col7\" class=\"data row13 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col8\" class=\"data row13 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col9\" class=\"data row13 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col10\" class=\"data row13 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col11\" class=\"data row13 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row13_col12\" class=\"data row13 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row14\" class=\"row_heading level0 row14\" >MSFT</th>\n",
       "                        <td id=\"T_0b76b_row14_col0\" class=\"data row14 col0\" >17.59%</td>\n",
       "                        <td id=\"T_0b76b_row14_col1\" class=\"data row14 col1\" >21.37%</td>\n",
       "                        <td id=\"T_0b76b_row14_col2\" class=\"data row14 col2\" >22.47%</td>\n",
       "                        <td id=\"T_0b76b_row14_col3\" class=\"data row14 col3\" >20.90%</td>\n",
       "                        <td id=\"T_0b76b_row14_col4\" class=\"data row14 col4\" >22.75%</td>\n",
       "                        <td id=\"T_0b76b_row14_col5\" class=\"data row14 col5\" >18.64%</td>\n",
       "                        <td id=\"T_0b76b_row14_col6\" class=\"data row14 col6\" >34.22%</td>\n",
       "                        <td id=\"T_0b76b_row14_col7\" class=\"data row14 col7\" >8.89%</td>\n",
       "                        <td id=\"T_0b76b_row14_col8\" class=\"data row14 col8\" >29.71%</td>\n",
       "                        <td id=\"T_0b76b_row14_col9\" class=\"data row14 col9\" >40.09%</td>\n",
       "                        <td id=\"T_0b76b_row14_col10\" class=\"data row14 col10\" >44.96%</td>\n",
       "                        <td id=\"T_0b76b_row14_col11\" class=\"data row14 col11\" >42.31%</td>\n",
       "                        <td id=\"T_0b76b_row14_col12\" class=\"data row14 col12\" >52.28%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row15\" class=\"row_heading level0 row15\" >NI</th>\n",
       "                        <td id=\"T_0b76b_row15_col0\" class=\"data row15 col0\" >10.83%</td>\n",
       "                        <td id=\"T_0b76b_row15_col1\" class=\"data row15 col1\" >12.00%</td>\n",
       "                        <td id=\"T_0b76b_row15_col2\" class=\"data row15 col2\" >10.47%</td>\n",
       "                        <td id=\"T_0b76b_row15_col3\" class=\"data row15 col3\" >12.53%</td>\n",
       "                        <td id=\"T_0b76b_row15_col4\" class=\"data row15 col4\" >10.43%</td>\n",
       "                        <td id=\"T_0b76b_row15_col5\" class=\"data row15 col5\" >12.69%</td>\n",
       "                        <td id=\"T_0b76b_row15_col6\" class=\"data row15 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row15_col7\" class=\"data row15 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row15_col8\" class=\"data row15 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row15_col9\" class=\"data row15 col9\" >5.26%</td>\n",
       "                        <td id=\"T_0b76b_row15_col10\" class=\"data row15 col10\" >3.35%</td>\n",
       "                        <td id=\"T_0b76b_row15_col11\" class=\"data row15 col11\" >3.89%</td>\n",
       "                        <td id=\"T_0b76b_row15_col12\" class=\"data row15 col12\" >0.99%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row16\" class=\"row_heading level0 row16\" >PCAR</th>\n",
       "                        <td id=\"T_0b76b_row16_col0\" class=\"data row16 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col1\" class=\"data row16 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col2\" class=\"data row16 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col3\" class=\"data row16 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col4\" class=\"data row16 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col5\" class=\"data row16 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col6\" class=\"data row16 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col7\" class=\"data row16 col7\" >9.39%</td>\n",
       "                        <td id=\"T_0b76b_row16_col8\" class=\"data row16 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col9\" class=\"data row16 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col10\" class=\"data row16 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col11\" class=\"data row16 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row16_col12\" class=\"data row16 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row17\" class=\"row_heading level0 row17\" >PSA</th>\n",
       "                        <td id=\"T_0b76b_row17_col0\" class=\"data row17 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col1\" class=\"data row17 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col2\" class=\"data row17 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col3\" class=\"data row17 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col4\" class=\"data row17 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col5\" class=\"data row17 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col6\" class=\"data row17 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col7\" class=\"data row17 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col8\" class=\"data row17 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col9\" class=\"data row17 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col10\" class=\"data row17 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col11\" class=\"data row17 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row17_col12\" class=\"data row17 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row18\" class=\"row_heading level0 row18\" >SEE</th>\n",
       "                        <td id=\"T_0b76b_row18_col0\" class=\"data row18 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col1\" class=\"data row18 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col2\" class=\"data row18 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col3\" class=\"data row18 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col4\" class=\"data row18 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col5\" class=\"data row18 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col6\" class=\"data row18 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col7\" class=\"data row18 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col8\" class=\"data row18 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col9\" class=\"data row18 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col10\" class=\"data row18 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col11\" class=\"data row18 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row18_col12\" class=\"data row18 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row19\" class=\"row_heading level0 row19\" >T</th>\n",
       "                        <td id=\"T_0b76b_row19_col0\" class=\"data row19 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col1\" class=\"data row19 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col2\" class=\"data row19 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col3\" class=\"data row19 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col4\" class=\"data row19 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col5\" class=\"data row19 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col6\" class=\"data row19 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col7\" class=\"data row19 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col8\" class=\"data row19 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col9\" class=\"data row19 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col10\" class=\"data row19 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col11\" class=\"data row19 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row19_col12\" class=\"data row19 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row20\" class=\"row_heading level0 row20\" >TGT</th>\n",
       "                        <td id=\"T_0b76b_row20_col0\" class=\"data row20 col0\" >7.18%</td>\n",
       "                        <td id=\"T_0b76b_row20_col1\" class=\"data row20 col1\" >4.75%</td>\n",
       "                        <td id=\"T_0b76b_row20_col2\" class=\"data row20 col2\" >8.91%</td>\n",
       "                        <td id=\"T_0b76b_row20_col3\" class=\"data row20 col3\" >5.86%</td>\n",
       "                        <td id=\"T_0b76b_row20_col4\" class=\"data row20 col4\" >9.26%</td>\n",
       "                        <td id=\"T_0b76b_row20_col5\" class=\"data row20 col5\" >11.20%</td>\n",
       "                        <td id=\"T_0b76b_row20_col6\" class=\"data row20 col6\" >14.02%</td>\n",
       "                        <td id=\"T_0b76b_row20_col7\" class=\"data row20 col7\" >15.63%</td>\n",
       "                        <td id=\"T_0b76b_row20_col8\" class=\"data row20 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row20_col9\" class=\"data row20 col9\" >1.35%</td>\n",
       "                        <td id=\"T_0b76b_row20_col10\" class=\"data row20 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row20_col11\" class=\"data row20 col11\" >0.49%</td>\n",
       "                        <td id=\"T_0b76b_row20_col12\" class=\"data row20 col12\" >0.29%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row21\" class=\"row_heading level0 row21\" >TMO</th>\n",
       "                        <td id=\"T_0b76b_row21_col0\" class=\"data row21 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col1\" class=\"data row21 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col2\" class=\"data row21 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col3\" class=\"data row21 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col4\" class=\"data row21 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col5\" class=\"data row21 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col6\" class=\"data row21 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col7\" class=\"data row21 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col8\" class=\"data row21 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col9\" class=\"data row21 col9\" >0.58%</td>\n",
       "                        <td id=\"T_0b76b_row21_col10\" class=\"data row21 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col11\" class=\"data row21 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row21_col12\" class=\"data row21 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row22\" class=\"row_heading level0 row22\" >TXT</th>\n",
       "                        <td id=\"T_0b76b_row22_col0\" class=\"data row22 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col1\" class=\"data row22 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col2\" class=\"data row22 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col3\" class=\"data row22 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col4\" class=\"data row22 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col5\" class=\"data row22 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col6\" class=\"data row22 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col7\" class=\"data row22 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col8\" class=\"data row22 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col9\" class=\"data row22 col9\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col10\" class=\"data row22 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col11\" class=\"data row22 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row22_col12\" class=\"data row22 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row23\" class=\"row_heading level0 row23\" >VZ</th>\n",
       "                        <td id=\"T_0b76b_row23_col0\" class=\"data row23 col0\" >4.27%</td>\n",
       "                        <td id=\"T_0b76b_row23_col1\" class=\"data row23 col1\" >5.99%</td>\n",
       "                        <td id=\"T_0b76b_row23_col2\" class=\"data row23 col2\" >3.00%</td>\n",
       "                        <td id=\"T_0b76b_row23_col3\" class=\"data row23 col3\" >6.25%</td>\n",
       "                        <td id=\"T_0b76b_row23_col4\" class=\"data row23 col4\" >2.63%</td>\n",
       "                        <td id=\"T_0b76b_row23_col5\" class=\"data row23 col5\" >3.68%</td>\n",
       "                        <td id=\"T_0b76b_row23_col6\" class=\"data row23 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row23_col7\" class=\"data row23 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row23_col8\" class=\"data row23 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row23_col9\" class=\"data row23 col9\" >8.18%</td>\n",
       "                        <td id=\"T_0b76b_row23_col10\" class=\"data row23 col10\" >7.65%</td>\n",
       "                        <td id=\"T_0b76b_row23_col11\" class=\"data row23 col11\" >8.32%</td>\n",
       "                        <td id=\"T_0b76b_row23_col12\" class=\"data row23 col12\" >0.72%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0b76b_level0_row24\" class=\"row_heading level0 row24\" >ZION</th>\n",
       "                        <td id=\"T_0b76b_row24_col0\" class=\"data row24 col0\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col1\" class=\"data row24 col1\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col2\" class=\"data row24 col2\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col3\" class=\"data row24 col3\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col4\" class=\"data row24 col4\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col5\" class=\"data row24 col5\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col6\" class=\"data row24 col6\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col7\" class=\"data row24 col7\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col8\" class=\"data row24 col8\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col9\" class=\"data row24 col9\" >0.03%</td>\n",
       "                        <td id=\"T_0b76b_row24_col10\" class=\"data row24 col10\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col11\" class=\"data row24 col11\" >0.00%</td>\n",
       "                        <td id=\"T_0b76b_row24_col12\" class=\"data row24 col12\" >0.00%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fcb09c4d220>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_s.style.format(\"{:.2%}\").background_gradient(cmap='YlGn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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aSytXrlS/fv1UVlamoqIiSdL999+v9u3bq7q6Wscee6zOOussdejQodbr58yZo7Fjx6Y0V1pkAAAAAOxUUVGRysrKtG3bNj3++OM655xzJEl33XWX+vXrp6FDh+rNN9/Uq6++Gn/NyJEjdeihh+qZZ57Reeedl9J8KGQAAAAASJL69Omj5cuXJz1WVFSkWbNm6ZlnnlFBQYEOPfRQLViwQM8884yee+45rVy5UgMGDNCWLVvirykvL9frr7+uPn36aMqUKSnNlUIG2EP5M/KjTgEAACAlTjrpJH355Ze1BuUvXbpUCxcuVF5enjp06KDi4uJ4t7JPPvlEhxxyiPbff3+tXbtWzz//fL1rZmdn684779SDDz6oDz/8MGW5UsgAAAAAkCSZmR599FHNnTtXeXl56tOnj0pKSnTEEUdIClpl1q5dq3HjxkmSTj/9dG3btk0FBQW66aabNHTo0KTXPfzww1VUVKSpU6emLFcG+wMA0FyVtJO6dY06CwAR2tl0yWE44ogjNGvWrKTHJk2apEmTJsW39913Xz399NNJz62qqqq1fffdd6csR4kWGQAAAAAZiEIGAAAAQMahkAEAAACQcShkAAAAAGQcChkAAAAAGYdCBgAAAEDGYfplAAAAAHFZWVnKz/96we/CwkJt2bJFX375pX71q1/F91dUVKioqEhr1qxJep2SkhJNnz5dOTk52rp1q2666ab4QpqpQCEDAAAANFMbixen9Hpdfn3iTs/Jzs5WRUVFrX3r1q3TqFGjahUyZWVlOu+88xq91qRJkzR58mS9+uqrGjRokM4++2y1adNmt3Kvq0ldy8zsdDNbZ2brzay4kfOONbPtZnZ2SrIDAAAAELljjjlGBx98sF544YX4vlmzZqmwsFDTp0/Xscceq379+umss87SF198Ue/13bt31/7776+PPvooZTnttJAxsyxJUyWNktRbUpGZ9W7gvN9I+lvKsgMAAACQVtXV1erfv3/8a+bMmZKkoqIilZWVSZKef/55dejQQd27d9f48eO1dOlSrVy5Ur169dJ9991X75ovvfSSunfvrkMPPTRleTala9kQSevdfYMkmVmZpDMlvVLnvKslPSLp2JRlBwAAACCtknUtk4KxMsOHD9ftt9+usrKy+HiXyspK/eQnP9HHH3+szZs367TTTou/5ne/+52mT5+uDRs2aM6cOSnNsyldyzpLejNhe2NsX5yZdZY0TtK9jV3IzK4ws2Vmtuz999/f1VwBAGjxOpVXqFN5RdRpAEA9Rx55pHJzc7Vw4UI98sgjOvfccyVJF198se655x6tXr1aN998s7Zs2RJ/zaRJk7Ru3TrNnDlTF154Ya1je6ophYwl2ed1tu+U9CN3397Yhdx9mrsPdvfBOTk5TUwRAAAAQHNQVFSkSZMmKS8vT126dJEkffbZZzr88MP11Vdf6aGHHkr6uvHjx2vw4MGaMWNGynJpSiGzUdKRCdtdJL1d55zBksrMrErS2ZL+28zGpiJBAAAAAOlTd4xMcfHXc32dc845evnll1VYWBjf9/Of/1zHHXecTjnlFPXs2bPB606ZMkV33HGHduzYkZI8mzJGZqmk7mbWTdJbkgol1Zpnzd271XxvZg9IetLdH0tJhgAAAEAr1ZTpklNt+/aGO1nl5OToq6++qrXve9/7nr73ve/VO7ekpKTW9qBBg7Ru3bqU5Cg1oZBx921mdpWC2ciyJN3v7i+b2cTY8UbHxQAAAABAqjVpQUx3f0rSU3X2JS1g3P3iPU8LAAAAABrWpAUxAQAAAKA5oZABAAAAkHEoZAAAAABkHAoZAAAAABmHQgYAAACAJGnSpEm6884749unnXaaLrvssvj2D3/4Q91xxx3Kzs5W//791bt3b1144YX1pmROhybNWgYAAAAg/equxRL29YYPH66HH35Y1113nXbs2KEPPvhAn376afz4kiVLdOeddyovL08VFRXavn27TjnlFM2aNUvnn39+SnPdGVpkAAAAAEiSjj/+eC1ZskSS9PLLL6tv37468MAD9dFHH+nLL7/UmjVrdMghh8TPz8rK0pAhQ/TWW2+lPVdaZAAAAABIko444gjtvffeeuONN7RkyRINGzZMb731lp577jm1a9dOBQUF2meffeLnb9myRS+88IJ+//vfpz1XWmQAAAAAxNW0ytQUMsOGDYtvDx8+XJL02muvqX///urQoYO6du2qgoKCtOdJIQMAAAAgbvjw4VqyZIlWr16tvn37aujQoXruuee0ZMkSHX/88ZIUHyOzfv16Pf/883riiSfSnieFDAAAAIC4448/Xk8++aTat2+vrKwstW/fXh9//LGee+45DRs2rNa5hx9+uH7961/rV7/6VdrzpJABAAAAEJefn68PPvhAQ4cOrbWvXbt26tixY73zx44dqy+++EKLFy9OZ5oM9gcAAACaq1RPv9wUWVlZtaZclqQHHngg/n1ubq4qKyvj22amlStXpiu9OFpkAAAAAGQcChkAAAAAGYdCBgAAAEDGoZABAAAAkHEoZAAAAABkHAoZAAAAABmHQgYAAABAnJnpggsuiG9v27ZNOTk5GjNmjKRgKuacnBwNGDBA3bt312mnnaYlS5bEz7/44ovVrVs39evXTz169NCFF16ot956K+V5so4MAAAA0EzNm5+X0uudfNJrOz2nbdu2qqysVHV1tbKzszV37lx17ty51jkTJkzQPffcI0kqLy/X+PHjVV5erl69ekmSfvvb3+rss8+Wu+vOO+/UyJEjVVlZqX322SdlPwstMgAAAABqGTVqlGbPni1JKi0tVVFRUYPnjhw5UldccYWmTZtW75iZadKkSerUqZOefvrplOZIIQMAAACglsLCQpWVlWnLli1atWqVjjvuuEbPHzhwoNauXbvbx3cHhQwAAACAWgoKClRVVaXS0lKNHj16p+e7+x4d3x0UMgAAAADqOeOMMzR58uRGu5XVWLFiRXx8zO4c3x0M9gcAAABQzyWXXKJ27dopPz9fCxYsaPC8hQsXatq0aSovL693zN11991365133tHpp5+e0vxokQEAIGIbixdHnQIA1NOlSxdde+21SY/NnDlT/fv3V48ePfTLX/5SjzzySK0Wl+uvvz4+/fLSpUtVXl6e0hnLJFpkAAAAgGarKdMlp9rmzZvr7RsxYoRGjBghKVgn5uKLL27w9Q888EA4idVBiwwAAACAjEMhAwAAACDjUMgAAAAAyDgUMgAAAAAyDoUMAAAAgIxDIQMAAAAg41DIALsht3h21CkAAACE5tFHH5WZae3atZKkqqoqZWdna8CAAerVq5eGDBmiGTNmxM9/4IEHlJOTowEDBqh79+467bTTtGTJklBzZB0ZAAAAoJnqVF6R0uu9O7J/k84rLS3VCSecoLKyMpWUlEiS8vLytGLFCknShg0bNH78eO3YsUP/8R//IUmaMGGC7rnnHklSeXm5xo8fr/Ly8loLZaYSLTIAAAAA4jZv3qxnn31W9913n8rKypKec/TRR+uOO+7QXXfdlfT4yJEjdcUVV2jatGmh5UkhAwAAACDuscce0+mnn64ePXqoffv2eumll5KeN3DgwHjXs905vqcoZAAAAADElZaWqrCwUJJUWFio0tLSpOe5e6PX2dnxPcUYGQAAAACSpE2bNmn+/PmqrKyUmWn79u0yM33/+9+vd+6KFSsaHf+ys+N7ihYZAECzUVJSEh9UCgBIvz//+c+68MIL9frrr6uqqkpvvvmmunXrpo0bN9Y6r6qqSpMnT9bVV1+d9DoLFy7UtGnTdPnll4eWKy0yAAAAACQF3cqKi4tr7TvrrLP0y1/+Uq+99poGDBigLVu26MADD9TVV18dn7FMkmbOnKl//OMf+uKLL9StWzc98sgjobbIUMgAAAAAzVRTp0tOlQULFtTbd8011+iaa65p9HUXX3yxLr744nCSagBdywAAAABkHAoZAAAAABmHQgYAAABAxmlSIWNmp5vZOjNbb2bFSY6faWarzKzCzJaZ2QmpTxUAAAAAAjsd7G9mWZKmSjpF0kZJS83sCXd/JeG0eZKecHc3swJJsyT1DCNhAAAAAGhKi8wQSevdfYO7b5VUJunMxBPcfbN/vXRnW0nhLuMJpNHG4sXaWLw46jQAAACQoCmFTGdJbyZsb4ztq8XMxpnZWkmzJV2SmvQAAAAApNO7776rwsJC5eXlqXfv3ho9erT++c9/Kjs7WwMGDFCvXr00ZMgQzZgxY6fXWrBggdq1a6cBAwaoZ8+emjx5csrybMo6MpZkX70WF3d/VNKjZvZNST+X9O16FzK7QtIVktS1a9ddyxQAAABoZXKLZ6f0elW//k6jx91d48aN00UXXaSysjJJUkVFhd577z3l5eVpxYoVkqQNGzZo/Pjx2rFjR61FMZM58cQT9eSTT6q6uloDBgzQuHHjdPzxx+/xz9KUFpmNko5M2O4i6e2GTnb3RZLyzKxjkmPT3H2wuw/OycnZ5WQBAGjJ5s3PizoFAK1ceXm52rRpo4kTJ8b39e/fX0ceeWSt844++mjdcccduuuuuyRJL774ooYPH64BAwZo+PDhWrduXb1rZ2dnq3///nrrrbdSkmtTCpmlkrqbWTcz20dSoaQnEk8ws2+YmcW+HyhpH0mbUpIhAAAAgLSorKzUoEGDmnTuwIEDtXbtWklSz549tWjRIq1YsUI/+9nP9OMf/7je+R999JFeffVVffOb30xJrjvtWubu28zsKkl/k5Ql6X53f9nMJsaO3yvpLEkXmtlXkqolTUgY/A8AAACghUm83f/kk0900UUX6dVXX5WZ6auvvoofW7x4sQoKCrRu3ToVFxerU6dOKYnfpHVk3P0pd+/h7nnu/ovYvntjRYzc/Tfu3sfd+7v7MHf/R0qyAwAAAJA2ffr00fLly5t07ooVK9SrVy9J0k033aSRI0eqsrJSf/3rX7Vly5b4eSeeeKJWrVql1atX6w9/+IMqKipSkmuTChkAAAAALd9JJ52kL7/8UtOnT4/vW7p0qV5//fVa51VVVWny5Mm6+uqrJQUtMp07BxMbP/DAA0mv3aNHD9144436zW9+k5JcKWSAJiopKYk6BaDFun3CmKhTAABIMjM9+uijmjt3rvLy8tSnTx+VlJToiCOO0GuvvRaffvncc8/V1VdfHZ+x7IYbbtCNN96o448/Xtu3b2/w+hMnTtSiRYv0r3/9a49zbcr0ywAAAAAisLPpksNwxBFHaNasWfX2V1dXN/iaYcOG6Z///Gd8++c//7kkacSIERoxYkR8f3Z2dlpnLQMAAACAZoVCBgAAAEDGoZABAAAAkHEoZAAAAABkHAoZAAAAABmHQgYAAABAxqGQAQAAABBXVVWlvn371tpXUlKi2267TZJ02223qWfPnurbt6/69eunBx98UFIw1fKyZcvSlifryAAAAADNVUm7FF/vkz16+b333qu5c+fqxRdf1EEHHaRPPvlEjz32WGpy20UUMgAAAACa5Je//KXKy8t10EEHSZLatWuniy66KJJc6FoGAAAAYKeqq6v12WefKS8vL+pUJFHIAAAAAEhgZkn379ixo8FjUaCQAQAAABDXoUMHffTRR7X2ffjhh8rNzVXbtm21YcOGiDKrjUIGAAAAQNwBBxygww8/XPPmzZMUFDFz5szRCSecoBtvvFFXXnmlPv30U0nSp59+qmnTpkWSJ4P9AQAAANTy4IMP6sorr9QPf/hDSdLNN9+svLw8fe9739PmzZt17LHHqk2bNmrTpk38nHSjkAEAAACaqz2cLnl39e7dW+Xl5fX2m5luuOEG3XDDDfWOLViwIA2ZfY2uZQAAAAAyDoUMAAAAgIxDIQMAAAAg41DIAAAAAMg4FDIAAAAAMg6FDAAAAICMw/TLAAAAAOKysrKUn58f3y4sLFRxcbFGjBihd955R/vuu6+2bt2qb3/727rlllt08MEHN3q93NxcHXjggTIzHXLIIXrwwQd11FFH7XGeFDIAAABAM5U/I3/nJ+2C1Ret3uk52dnZqqioSHrsoYce0uDBg7V161bdeOONOvPMM7Vw4cKdXrO8vFwdO3bUzTffrFtuuUXTp0/f1dTroWsZAAAAgF2yzz776NZbb9Ubb7yhlStXSpLGjh2rQYMGqU+fPpo2bVrS1w0bNkxvvfVWSnKgkAEAAAAQV11drf79+8e/Zs6cmfS8rKws9evXT2vXrpUk3X///Vq+fLmWLVumu+66S5s2bar3mjlz5mjs2LEpyZOuZQAAAADiGutaVpe7x7+/66679Oijj0qS3nzzTb366qvq0KGDJGnkyJF67733dOihh+qWW25JSZ60yAAAAADYZdu3b9fq1avVq1cvLViwQM8884yee+45rVy5UgMGDNCWLVvi55aXl+v1119Xnz59NGXKlJTEp5ABAAAAsEu++uor3XjjjTryyCNVUFCgTz75RIcccoj2339/rV27Vs8//3y912RnZ+vOO+/Ugw8+qA8//HCPc6CQAQAAABBXd4xMcXFx/Nj555+vgoIC9e3bV59//rkef/xxSdLpp5+ubdu2qaCgQDfddJOGDh2a9NqHH364ioqKNHXq1D3OkzEyAAAAQDPVlOmSU2379u1J9y9YsKDB1+y77756+umnkx6rqqqqtX333Xfvbmq10CIDAAAAIONQyAAAAADIOBQyAABEYOrE+VGnAAAZjUIGAAAAaEYS12ZpLXbnZ6aQAQAgjfJn5EedAoBmbL/99tOmTZtaVTHj7tq0aZP222+/XXods5YBAAAAzUSXLl20ceNGvf/++1Gnklb77befunTpskuvoZABAAAAmok2bdqoW7duUaeREehaBgAAACDjUMgAACLF7F0AgN1BIQMASJvc4tlRpwAAaCEoZAAAaZc/I791zt5V0i7qDACgxaCQAQAAAJBxKGQAAEizNT17RZ0CAGS8JhUyZna6ma0zs/VmVpzk+Plmtir2tcTM+qU+VQAAAAAI7LSQMbMsSVMljZLUW1KRmfWuc9q/JH3L3Qsk/VzStFQnCgAAAAA1mtIiM0TSenff4O5bJZVJOjPxBHdf4u4fxTafl7Rry3ICAAAAwC5oSiHTWdKbCdsbY/sacqmkp/ckKQAAAABozN5NOMeS7POkJ5qNVFDInNDA8SskXSFJXbt2bWKKAAAAAFBbU1pkNko6MmG7i6S3655kZgWS/p+kM919U7ILufs0dx/s7oNzcnJ2J18AAAAAaFIhs1RSdzPrZmb7SCqU9ETiCWbWVdJfJF3g7v9MfZoAAAAA8LWddi1z921mdpWkv0nKknS/u79sZhNjx++VNEVSB0n/bWaStM3dB4eXNgAAAIDWrCljZOTuT0l6qs6+exO+v0zSZalNDQAAAACSa9KCmAAAAADQnFDIAAAAAMg4FDIAAAAAMk6TxsgAAIDUu33CGEnShG4/ijgTAMg8tMgAAAAAyDi0yAC7q6Rd8N9uXaPNAwAAoBWiRQYAAABAxqGQAQAAAJBxKGQAAM1Sp/KKqFMAADRjjJEBACBkucWzJUlV+0WcCAC0ILTIAAAAAMg4FDIAAAAAMg6FDAAAAICMQyEDAAAAIONQyABAxNb07BV1CgAAZBwKGQAAAAAZh0IGAAAAQMahkAEAAACQcShkAAAAAGQcChkAAAAAGYdCBgDQLGwsXhx1CgDSoKSkRCUlJVGngRaAQgYAAABAxqGQAQA0byXtos4AANAMUcgAAAAAyDgUMgAQFVoaAADYbRQyAAAAADIOhQwAAACAjEMhAwAAACDjUMgAANIrYWzQmp69IkwEQLqxXhRSiUIGAAAAQMahkAF2UafyiqhTAAAAaPUoZAAAAABkHAoZAAAAABmHQgYAAABAxqGQAbBT8+bnad78vKjTAAAAiKOQAQAAAJBxKGQAAGilbp8wJuoUAGC3UcgAANCKrOnZi4VIAbQIFDIZhCdnAAAAQIBCBgAAAEDGoZABAKA1KGkXdQYAkFIUMgAAAAAyDoVMM5RbPDvqFAAAAIBmjUIGAAAAQMahkAEAAEDomH0VqUYhAwAAACDjUMgAANDCMfYSQEvUpELGzE43s3Vmtt7MipMc72lmz5nZl2Y2OfVptm5TJ87X1Inzo04DAAAAaDZ2WsiYWZakqZJGSeotqcjMetc57UNJ10i6LeUZAgCAlMifkR//ngdkADJdU1pkhkha7+4b3H2rpDJJZyae4O7/dvelkr4KIcdWK/EDBwAAAMDXmlLIdJb0ZsL2xtg+AAAAAIhEUwoZS7LPdyeYmV1hZsvMbNn777+/O5cAAAAAgCYVMhslHZmw3UXS27sTzN2nuftgdx+ck5OzO5cAAAAAgCYVMksldTezbma2j6RCSU+EmxYAAAAANGynhYy7b5N0laS/SVojaZa7v2xmE81soiSZWScz2yjpB5J+YmYbzeygMBNv8UraRZ1Bq8eMPgAQvpKSEpWUlESdBoAMtHdTTnL3pyQ9VWffvQnfv6ugyxmQ8fJn5Gv1RaujTgMAgBaDh4MIQ5MWxER01vTsFXUKAAAAQLNDIQMAEWK9KNSgexVamvwZ+bzHIVRN6loGAEid3OLZkqSq/SJOBACADEaLDKCvbyyBqEydOJ8+5AAA7AIKGQAAAKA1yvBZcilkAAAAgFakU3lF1CmkBIUMAAAAgIxDIQMAAAAg41DINKSkXcb3GwQAAACSaQkTHVHIAI24fcKYqFMAWrWW8EELAAgHhQxQg1Y4AAD2GA8gkC4UMgAAAAAyDoXMHmop09cBAAAAmYRCBgAAAEDGoZABAAAAkHEoZJpgTc9eOz+JgeIAAABA2lDIJMFsGwAAAMhUa3r2atqD+AxHIQMk0Rr++AEAQAvTynoHUcgAAAAgNDwcRFgoZAAAAABkHAoZIAOUlJREnQIAAECzQiEDAADiWOgZQKagkAGQ1O0TxkSdAgAAQIMoZAAAAABkHAqZDNapvIIuAAAAoPlpZdMAIxoUMhlmY/HiqFMAAAAAIkchsxP5M/KjTqFpePIBAADQauUWz446hbSjkAEAAACQcShkmmjqxPlRpwAAAAAghkIGaOVaY1M0gCagyzKAZo5CBgAAAGihWvK6cBQyAAAAADIOhQyA3ZIxM/oB2GV0OQWQCShkAAAAAGQcChkAAACghWhNPSYoZFKAJnhkPGYnAgAAGYZCBgAAAGiBWvo6iBQyAOLW9OylNT17RZ0GAADATlHIAAAAAMg4FDIAAAAAMg6FDAAAAICMQyEDAAAAIONQyOyijcWLtbF4cdRpAJHoVF4RdQoAAACSKGQAAAAQER6QYU9QyOyBefPzok4BSJnWtBIwAADIfBQyAOrZ6QJaJe3SkwiASPGAA0Bz1qRCxsxON7N1ZrbezIqTHDczuyt2fJWZDUx9qgCag9zi2VGnAAAAUiSTH1jstJAxsyxJUyWNktRbUpGZ9a5z2ihJ3WNfV0j6Q4rzBAAAQEsVQUs/43MyX1NaZIZIWu/uG9x9q6QySWfWOedMSQ964HlJB5vZ4SnOFQAAAAAkNa2Q6SzpzYTtjbF9u3oOAAAAkFT+jPyM7uaE9DN3b/wEs3Mknebul8W2L5A0xN2vTjhntqRfufs/YtvzJN3g7svrXOsKBV3PJOkYSev2IPeOkj7Yg9fvidYaO+r4xG598Ynd+uITu/XFJ3bri0/s1hd/T2If5e45yQ7s3YQXb5R0ZMJ2F0lv78Y5cvdpkqY1IeZOmdkydx+cimsROzPiEzsarfVnb62xo45P7Gi01p+9tcaOOj6xo9ESf/amdC1bKqm7mXUzs30kFUp6os45T0i6MDZ72VBJn7j7OynOFQAAAAAkNaFFxt23mdlVkv4mKUvS/e7+splNjB2/V9JTkkZLWi/pC0n/EV7KAAAAAFq7pnQtk7s/paBYSdx3b8L3LunK1Ka2UynpokbsjIpP7NYXn9itLz6xW198Yre++MRuffFDib3Twf4AAAAA0Nw0ZYwMAAAAMoyZNannDZCpKGQAAABaphejTgAIE4UMAABAy2SRBjcbH2X8qJjZA1Hn0Fpk5BgZM8uTVCSp0N37RpTDkbH4vw0xxl7uvqOBYwe7+8dhxY7FGOruz4cZY1eY2X6SvuvuD0edS0tlZie5+/zY993c/V8Jx8a7+1+iyy4cZvZXSQ2+Ebr7GSHGvqux4+5+TVixE3Jo4+5fhR2ngdinSTrQ3f9cZ//5kv7t7nOjyCtsZnaVu98TdR7NjZkd5e6vRxQ71L8DMzvI3T9t4FhXd38jpLgbJd3R0HF3b/BYiuK/5O4Dw4yxk/h9Jd0gqbeC9/lXJN3u7qtCjhv1z32MuydddN7Mjnf3Z9OdU1gypu+kmR0uaYKk8yQVSPqVgmImnTl0lHROLG5nSY+GHHKZmX3P3V+ok8dlkn4s6eiQ4//BzF6U9KOwi6aGmFmWpFMV/D8/TdJiSaEWMmZ2nILZNfIkrZZ0qbu/EmbMhNjdJf2XpA8VfPhMl/RNBVObX+buS0NO4TZJNW++jyR8L0k/kRRqIRP7O79SwYeOJC2T9H/dfVOIYW8L8do7M1FSpaRZChYRjuLp6Vtm9rikUknlnt6nWz+V9N0k++cpeH8NtZCJ6iZH0iWSIitkzOwHjR1Pw83tMAWfoYvc/d9mViCpWNKJqr24dqjMzCSNVHBf8V1Jh4UYboFi76dmNs/dT0449phqv9emUpakAxRxy0wUzOxMBe/vv4r91yQNkvSImU1298dDDL+/mQ1QA//f3f2lEGNL0hoz+6OkK919c51jdyu83zeZ2Wf6+uFgzc/vCmqOfdw9pbVHsy9kzOxyBTexXRR82F8m6XF3/2ma4h8oaZyCN7oeCj5cj3b3LmkIf42kaTXFhKSjJP23pI0Kbm7DNiiWw4tm9nN3/2MaYkqSzOybCv6ff0dBH9/jJXVz9y/SEH6qpMmSFkk6Q9LvFBRR6fA/kh6UdJCkFyRdp+D370QFNz7HhRzfGvg+2XZqA5t9S9L/Srpf0gOxeAMlzTezsZJ+5u4XhBD6FUk5dYtVM+sj6d8hxEt0uIKHIxMkbZM0U9Ij7v5RyHET9ZJ0tqSbJD1oZn+WVFr3AUpI9nf39+vudPd3zaxtmIEjvsmJ2oFRBTaz30oaI6lC0o/M7ElJ35f0SwUFXjpyOE7B58s4Se0VPDy5PuywCd+3b+RYqr3j7j8L8fo709PMkj0YMAWrdxSEGPtnkk5x96qEfSvNbL6kx2NfYeks6XYl/7d1SSeFGFuSXlZwr/iSmV1Yp3dNqJ/l7l7r/SV2H/19Sf+pMBoA3L1Zf0naKmmhpMEJ+zakMX51LP6J+rorXjrjZ0m6RdJHkt6UdGoE/wa9JX0i6TNJn9b8N8R4GyUtkXSBgm4nkvSvNP68LzW2HXLsioTv1zd0LB0/e7r/PygoWAck2d8/9ns3I6S4ZZK+lWT/aZL+lMZ/+84KCui3JV2Qrrh1cjhC0rWSnpP0mqRfhBzvn5L2TrK/jaRXQ469UlJukv25klaGHHtb7He67leo763N4UvBg4P9Yt8fEvuM7Z6m2L+Q9KqCFr/LJHVI12dLVO+tklZE/O/9soKHsEm/Qo79yu4cayH/31+K/bemR8cUSXslHktDDgdLKpG0QcF9bIcw4jT7FhkFH6znSLrDzA5T0CrTJo3xfyypUNIfJP3JzGamMbb0dVe2P0j6tqQJZrbM3T9MR3Azu1RBk/9/SZrqsd/OkD0iaayCp9TbY91e0tnd5eA6AxRrbXu440QSx0TV7U+ddLxUih1tZk8oeGJT871i291Cjn2Au6+ou9PdK8zsPUn/EVLcfHdfmCTu38zs9pBi1mJmAxX8nZ8i6WlJy9MRty53f9vM7lPw4OQHCm72/ivEkH+RND02ZuRzSYq1xNylkLsxSmrjtZ/USpLcvcrMwv6MWe3uA0KO0SAzm9LIYXf3n4cYvtrdt8QCfWRm69z91RDjJbpC0joFn6dPuvsWM0vXZ8uhsS59lvC9Yts5IcY9eeenhGqrRzTuSdJXycYfmdlRCh4mtGQmSe6+yMwGK+jNszg2/jDcwMEwjB8quIe7X8EDyk9Ci5ee+9LUMLMuCoqKIkn7S3rU3X+cpthHx+IWSuou6eZY/H+GGPMZBU+rrnH3f8X6814laZKkX7t7qCu0mtkSSVWSfuDu74YZK0nsmr7LRZJGK+hqdamkp7x+f89Ux/6fRg67u4fW/cHMvlDw9MQUjNFZX3NIQZfGsLvbfKux48lu+FMYe42k4V6nW5WZtZf0rLv3CinuP929RwPH1rn7MWHEjV3/pwq62axR0DI0x93T/gFbM5GGgr+34yXNieXzd3ffHmLcvRU8qbtM0usKfs+PlHSfpJs83MHXKxVMHpLsJuevHmKXFzNbEXEh88Mku9sqeI/t4O4HhBj7YwXddmt8M3Hbw51cI3HM5UmSyhU8IDwy7L87M7u5seOepu7y6WZm97j7VRHFHivpVgXdFpcreCB6rIKHsz9y98dCjH2BN9Ad38xOdPfFYcWOxag32YCZXaTg/XZ/d+8QYuzPJb2voKv8Z3WPe4rH4GVEIRP7ZfyGgqdYf4vtO0bBrGFp/+M3s3wF/WvPdfe8EOOMc/d6/QnNrJOk29z9/4QVOxbnFG8GswbFno6eruDD51R37xhxSqGJ3UQ1KJ1PtswsJxaz3hiGkOJdIelyBd2ragZCDpL0G0n3hVW4m9lsBa2NT9XZP0rBQ4RRYcSNxdihoNm9OrYrcYCkh3kznZDDnxTczC1SULw8WfPEPF3MLFvBe7wUdKmsbuz8FMUcq+hucm4KudWjyWL9169VUMTMUjDZQWhjw6J8WFInj/0UPEQ4T0HxPs/dz0tH7NYk9nfW2d2nxrZf0NctUD/ykGchNbN+CloH+ih4X31Zwf3TypDjbpB0r6Q7aorkWK+i2yUd4+7Hhhx/h6QT3H1Jnf1HS7rB3SeGGLtEjc8EmtL79mZfyJjZfyv4BVyioIn0r1F/AMSazTalqZtVsvihT/0cixP51LAJuRwi6WMFfatDvckxswsbOewNPWVJYfyxqlO4p0usJWyKpKsVvOnvpaAJ/m5Pw4BRMxujYBapPvp6FqnfuvtfQ4zZQ9KTCt5jarp0DZY0TNKYkFtdIy9cY0/p/uLu9Z6cpSF2o2tMhNyNM8qbnPjTUjO7292vDjNeAzm0V9B98HxJMyT9vm5raJrzScvnWgOxD5Q03t1nhBhjlrufG/v+N+7+o4Rjf3f3U8OKHSUze1bBv+ubse0KBfdybSX9j9eeva3FMLODFTyEG67gQUG+gr+3WyX9wRtYWiOF8a9T0LXrcAWTyJS6e0WYMaOSCYVMpaR+7r7dzPaXtNjdB6Ux/lBJv1YwHe7PJf1RUkcFN3gXuvucNOVRb+pnd58ccsytamRq2LDe9GP9t2e5+1oz21dBN5d+Cm6oz3P3Z8KImxD/7mS7FXS96ewpnjqwTuxIC3czm6SgK98VHltDJvYE5w8Kuj39Lg05dHT3D8KOUyfmvgqezPaJ7XpZwUD/L9MQe6wiKlxj8X+o2k/PXNIHkv7hCesIhRR7h4LZqypqdiXmEWY3zigldi1L1gUkDfF/K2m8gmnmp4bdXbeRPNL6uWZmx0p6s6ardOyh1VkKujWWeIhjTxv7N4+6q2GYzGxpYutDYlczM3ve3YeGGPuJxo6H2Y0xIYdrFcx8+rakoe6+MeyYdeIfpWBIRKGk/RRMs1/qIY9Li/VouFG1p7b/Td2eDymJlQGFTN0/+LS+6ZvZMgUD/tspeNMf5e7Pm1lPBb8Mob35WPKpnyd4eqZ+lpl1UARTw5rZy5L6urvHuhsVKej60kPBzFVDwoxfJxdT8MTyRwr+EH/hIa4x0QwK9xUKpqv8oM7+HAXjJcL8ff+ugoGBXymY2ODcus3iIcWtmfO+7pSULulLBbN3/Ze7zwshduQtzg303W+vYNa2EncvCzH2OAXvL99QMBVqqbuvb/xVKYsd2U1OnRaZKAqZHQp+t7epdhFb06XxoBBjR/a5ZmYvSfq2u39owRT/ZQpan/tL6uXuZ4cZu6F/8yh+B9LFzNa7+zcaOPaah9s9/30Fs72WKljOoO7D2DDHfB6soEXmOAW9DEYreI+/1mOLTqebBeva3C+pwN2zQoxzuYKplm9QsBacFPRy+LWk/5fybuIe4fRwTfmS9IWkVbGv1QnbqxXyFJmx+BUJ36+pc2xFyLEjnfq5Ti5pmxo28f+rghnM/jNhO13TBu6tYADyGgVrmhyTpriRTf0ci1e5O8dSFHuVpJ6x74+TtDCdP3sDOWUpaA0M5WdX0OKZFft+f0nLo/6ZE3Jrn8a/t7YKbmwfl/QPJZkOO4SY7ysYi3W9ggHn30r8Cjl24udY3c+4VVH/24f8s0f2uZZ4z6BgvbCShO2KkGOvlTRAwbi/NQrWyBpYsx31v0uIP/dDki5Psv8/FTy4CDN2loLxtTMkrVAw0L1Pmn7u12L3THsn7Ouv4KFVqD93nTzaKOhN8pCkdxU8kB4bcsxXJLVPsr9DGL/rmTD9crKZikzBApnpmLEssR9j3bEZYTdnRT31syTJ0j817JcWrLj9nqSRCt4MauwfcmyZ2ZUK+rTOk3S6p3fqyMTFw0xSXsK2PPzB31t381gqbHP3tZLk7i/EntxGyoMZu1Y20N0wFbbGYsjdv4i1ADYLHjy1Tlc+WxSsVfWppK4KukCErZOC97QiBUXUbAU3GC+nIXYoM/BliCg/17LMbG8PBl+frGA65hph3w+9o68XSHxXwSKsNdI6K2iaTZL0mJmdp9qTuOyrYJmF0MTeW+dImhPrPlwkaYGZ/czdw3pPTwjvt9XZUSFpeKzFIlRmVvPeVrOoeJmCLuOfhx1bwQOKet003X1TGB8pzb5rWSIz66/YbGGS/qWgm9M9IcfcLulzBW8+2Qqenim2vZ+7h76mjUUw9XMsbiRTw8bGJT2gYGaTOz3W1cbMRitoDSoKOf4OBSu6v68kxWqYxYSZdZd0mILm8ERHSXrbQ+52k/D7Xu+QQv59N7ONkhKnZfxB4raneMrG5sDMqhUs0Ffz7l4z5XbaZi1rJLeTJP3E3UNbgdrMaqZYHyLpGUll7r6s8VeFkkfNTc5vJaXjJqdu/A4KWoXecPdI1hBKtyg+18zsvxR08flAQcE80N3dzL6hoNvy8SHGHqJgfM47se2LFIzPqVLI43OiVNNtzsxOVjBeQpJe9jR1r4r9bX9Hwe9arqQnJN3v7m+FHDfS7oJmVi7pTwruk9P6u2XBzHRXeJ1JU2KTq0z3FA8PaPaFjAUzCtWsHbNJQbPYZHdvdLaflsrSNPVzLFbkU8NGIcpiwsyelPRjrzMOx4IFrW529++GFTtqDYzViPMWuM5CbCBmY9NUvtHQsRTmsDpJDu0VdCO9sKaVLKTYOxR0qfpHLIdaeXjIMyNGeJPzpKRid680s8MVPKlepqCQnebud4YZv7mJfa4VKRgrE/bn2lAFMzn93b9ehLWHggV5X2r0xXsWN7LxOVGKciIDM5shqa+CniRl7l6Zxth1H8zV0hIfzNUwsxMUdGX7H9We2v4iSf/H3f+R0ngZUMjskLRY0qU1N5BmtsHdj442s2hYGqd+toimhrVgxeNP3P2+OvuvVjCe4M4w4ibEiayYMLNKd+/bwLHV7p4fVmykX8JEA8mEOtFAQg51/85dwXvM52Z2XZh/b2Z2sRov5MKcDjfKm5yX3b1P7PsfKxgbdmGsO+WzLfUhkSTFWj8Oc/dn6+z/psJ/ULSfpImKzRKoYH2qtCxAa2Yr3b1f7Pupkt5395LYdoW7909HHukW5Q197P6xpodBuie1eEdB98mkfala4oO5RBasd/h91Z7afqqHsLh6JoyROUtBi0y5mdWsNt1s+pGHyRqZ+tnMQp/6OVmhkqZC6hIFgyDrmiZpqaQ7Q4wtSbl1ixhJcvdlZpYbcuzGxgZkhxw7UtaM1i1KF3dvcByQBauQ91XwZCtpcZuiHBp7IPEDhfj35u4PhHXtJrhAwU1OD0nXJPTdDv0mR8HMfDVOljRdQdDPYjdfLdmdSj6+9QsF09SG2eo8Q8H/+8WSRino6nRtiPESRTk+J0pZkg5QNPdtK6NqDZL0jqdh7bXmKlawTElHrGb/x+PByvaPmllbBQPDJkk6zMz+oKA/7d+jzC9k9+jrqZ/nq87UzwoGsYUmwkLK3b3ewHJ3/zJNg4+jLCaWmtnl7j49caeZXarwJ1mIWuLP91MFfeZbLQ9/ooGmCPXvzSKcAtnd9wrr2k3wZqyFeaOChzZzJMnMshXMMtSSRfmgqHdNq7aZ3adgEHS6lEpaaGYfKOiuvTiWxzcUTHTRUkV5Qx9ll6NW8cA9mQa6K0shDUto9oVMjVhf1ockPWTBisTnSCqW1JILmb1rCrXYLBvPS5IHC0WmI35khZSZHebu79XdF1a8OqIsJq5TULifr9qrzO+jYO2FFiuxG1GsS1No3Yoyibv/3yjDh3z9YWpknYcW7FJJP1OwPtYEd/84tn+ogn7lLVmUD4riLWHuvi2dkwS6+y/MbJ6+Hp9T87e1l4KxMi1VlH/Th8a6qicV8jiVk0O8dnM3VcH9YbLPjwmpDtbsx8i0ZhbxAlqJ/XbNbI2790o4FtoAPgtWW75G0g9Ve7rGWxX0sQz1BjdWMD2qYLrhesVEGH08k+QwUl93J0rbDC/NRdQzvrQmjYzTMUnZ7h7aA69Y97maaUILlN4pkBEBMyuVNL+BB0WnunvKb3QSYiTOypg4E2k6uhO2SmbW3iOaka21j1OJSuzvbKGCWWbfqnMs5Z/tFDLNmEU89XOUhZSZjVLQ4lZzM18p6dfu/nRYMZPk0KqLiShRyLQ+FvEUyOkUZZe6qDWHB0VoHfgciYaZrZD03wrGyPzA3R9OPJbqh+AUMmhQ1IUUWpc6LQP7q/bvG09LW6iopkCOkpm9r0a61Ln7wijySiceFCFsUU793JrZ12sH9VAwJKRS0pUeLPqc8uIyY8bIIP3cPSuKuK1x9io0PoMXWqY6UyD/NJ1TIEesk77uUneeWlGXuiinQEar05rHqUTO3f9pZsMk3SJpRWzYQMrRIoNmx8y2KqjgZylYlK/u00oGgQMtQJTrPDQXralLnSSZ2UzVngK5yt2vizQpACmTrCXMzEZIul9STqofWtIig+bocAWz0k2QtE3STEmPuPtHkWYFIKUingI5Ukm61N0l6S9R5pQmUU6BDCB89SZRcPcFZjZI0n+mOhgtMmjWzKyzgg/6H0j6kbv/MeKUAGCP1OlSV9aKutRFMgMngJaLQgbNlpkNVFDEnKJgdpvb3f2VaLMCgD3TmrvUMQUygFSikEGzY2Y/lTRG0hpJZZLmMBgUAAAAiShk0OzEnlZukFQd21Xrl9TdC9KeFAAAAJoVBvujOTpG0mEK1llIdJSCWcwAAADQyrXaGWPQrP1O0qfu/nril4J+1L+LODcAAAA0AxQyaI5y3X1V3Z3uvkzBNKUAAABo5Shk0Bzt18ix7LRlAQAAgGaLQgbN0VIzu7zuTjO7VME0zAAAAGjlmLUMzY6ZHSbpUUlb9XXhMljSPpLGufu7UeUGAACA5oFCBs2WmY1UsPq1JL3s7vOjzAcAAADNB4UMAAAAgIzDGBkAAAAAGYdCBgAAAEDGoZABAAAAkHEoZAAAAABkHAoZAAAAABnn/wPuxDd+wa+ARwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plotting a comparison of assets weights for each portfolio\n",
    "\n",
    "fig = plt.gcf()\n",
    "fig.set_figwidth(14)\n",
    "fig.set_figheight(6)\n",
    "ax = fig.subplots(nrows=1, ncols=1)\n",
    "\n",
    "w_s.plot.bar(ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Constraints on Assets and Assets Classes\n",
    "\n",
    "### 4.1 Creating the constraints\n",
    "\n",
    "In this part I use dictionaries to create the constraints but is prefered to create the tables in excel and upload them with pandas.read_excel."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Disabled</th>\n",
       "      <th>Type</th>\n",
       "      <th>Set</th>\n",
       "      <th>Position</th>\n",
       "      <th>Sign</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Type Relative</th>\n",
       "      <th>Relative Set</th>\n",
       "      <th>Relative</th>\n",
       "      <th>Factor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>False</td>\n",
       "      <td>All Assets</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>10.0000%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>Classes</td>\n",
       "      <td>Industry</td>\n",
       "      <td>Financials</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>20.0000%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False</td>\n",
       "      <td>Classes</td>\n",
       "      <td>Industry</td>\n",
       "      <td>Utilities</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>20.0000%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>Classes</td>\n",
       "      <td>Industry</td>\n",
       "      <td>Industrials</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>20.0000%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>Classes</td>\n",
       "      <td>Industry</td>\n",
       "      <td>Consumer Discretionary</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>20.0000%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Disabled        Type       Set                Position Sign   Weight  \\\n",
       "0     False  All Assets                                     <= 10.0000%   \n",
       "1     False     Classes  Industry              Financials   <= 20.0000%   \n",
       "2     False     Classes  Industry               Utilities   <= 20.0000%   \n",
       "3     False     Classes  Industry             Industrials   <= 20.0000%   \n",
       "4     False     Classes  Industry  Consumer Discretionary   <= 20.0000%   \n",
       "\n",
       "  Type Relative Relative Set Relative Factor  \n",
       "0                                             \n",
       "1                                             \n",
       "2                                             \n",
       "3                                             \n",
       "4                                             "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import riskfolio.ConstraintsFunctions as cf\n",
    "\n",
    "asset_classes = {'Assets': ['JCI','TGT','CMCSA','CPB','MO','APA','MMC','JPM',\n",
    "                            'ZION','PSA','BAX','BMY','LUV','PCAR','TXT','TMO',\n",
    "                            'DE','MSFT','HPQ','SEE','VZ','CNP','NI','T','BA'], \n",
    "                 'Industry': ['Consumer Discretionary','Consumer Discretionary',\n",
    "                              'Consumer Discretionary', 'Consumer Staples',\n",
    "                              'Consumer Staples','Energy','Financials',\n",
    "                              'Financials','Financials','Financials',\n",
    "                              'Health Care','Health Care','Industrials','Industrials',\n",
    "                              'Industrials','Health care','Industrials',\n",
    "                              'Information Technology','Information Technology',\n",
    "                              'Materials','Telecommunications Services','Utilities',\n",
    "                              'Utilities','Telecommunications Services','Financials']}\n",
    "\n",
    "asset_classes = pd.DataFrame(asset_classes)\n",
    "asset_classes = asset_classes.sort_values(by=['Assets'])\n",
    "\n",
    "constraints = {'Disabled': [False, False, False, False, False],\n",
    "               'Type': ['All Assets', 'Classes', 'Classes', 'Classes',\n",
    "                        'Classes'],\n",
    "               'Set': ['', 'Industry', 'Industry', 'Industry', 'Industry'],\n",
    "               'Position': ['', 'Financials', 'Utilities', 'Industrials',\n",
    "                            'Consumer Discretionary'],\n",
    "               'Sign': ['<=', '<=', '<=', '<=', '<='],\n",
    "               'Weight': [0.10, 0.2, 0.2, 0.2, 0.2],\n",
    "               'Type Relative': ['', '', '', '', ''],\n",
    "               'Relative Set': ['', '', '', '', ''],\n",
    "               'Relative': ['', '', '', '', ''],\n",
    "               'Factor': ['', '', '', '', '']}\n",
    "\n",
    "constraints = pd.DataFrame(constraints)\n",
    "\n",
    "display(constraints)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "A, B = cf.assets_constraints(constraints, asset_classes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 Optimize the portfolio with the constraints"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.7276%</td>\n",
       "      <td>10.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.7594%</td>\n",
       "      <td>10.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0767%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.4405%</td>\n",
       "      <td>9.7234%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA      BAX     BMY   CMCSA      CNP     CPB      DE  \\\n",
       "weights 0.0000% 3.7276% 10.0000% 0.0000% 1.7594% 10.0000% 0.0000% 9.0767%   \n",
       "\n",
       "            HPQ     JCI  ...       NI    PCAR     PSA     SEE       T     TGT  \\\n",
       "weights 0.0000% 0.0000%  ... 10.0000% 0.0000% 0.0000% 0.0000% 0.0000% 9.4405%   \n",
       "\n",
       "            TMO     TXT       VZ    ZION  \n",
       "weights 9.7234% 0.0000% 10.0000% 0.0000%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "port.ainequality = A\n",
    "port.binequality = B\n",
    "\n",
    "model = 'Classic'\n",
    "rm = 'MV'\n",
    "obj = 'Sharpe'\n",
    "rf = 0\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plf.plot_pie(w=w, title='Sharpe Mean Variance', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                  height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Industry</th>\n",
       "      <th>weights</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>APA</th>\n",
       "      <td>Energy</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BA</th>\n",
       "      <td>Financials</td>\n",
       "      <td>3.7276%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAX</th>\n",
       "      <td>Health Care</td>\n",
       "      <td>10.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BMY</th>\n",
       "      <td>Health Care</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CMCSA</th>\n",
       "      <td>Consumer Discretionary</td>\n",
       "      <td>1.7594%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNP</th>\n",
       "      <td>Utilities</td>\n",
       "      <td>10.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPB</th>\n",
       "      <td>Consumer Staples</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>Industrials</td>\n",
       "      <td>9.0767%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HPQ</th>\n",
       "      <td>Information Technology</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JCI</th>\n",
       "      <td>Consumer Discretionary</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPM</th>\n",
       "      <td>Financials</td>\n",
       "      <td>6.2724%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LUV</th>\n",
       "      <td>Industrials</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MMC</th>\n",
       "      <td>Financials</td>\n",
       "      <td>10.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MO</th>\n",
       "      <td>Consumer Staples</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>Information Technology</td>\n",
       "      <td>10.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NI</th>\n",
       "      <td>Utilities</td>\n",
       "      <td>10.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCAR</th>\n",
       "      <td>Industrials</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PSA</th>\n",
       "      <td>Financials</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEE</th>\n",
       "      <td>Materials</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T</th>\n",
       "      <td>Telecommunications Services</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TGT</th>\n",
       "      <td>Consumer Discretionary</td>\n",
       "      <td>9.4405%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TMO</th>\n",
       "      <td>Health care</td>\n",
       "      <td>9.7234%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TXT</th>\n",
       "      <td>Industrials</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VZ</th>\n",
       "      <td>Telecommunications Services</td>\n",
       "      <td>10.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZION</th>\n",
       "      <td>Financials</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Industry  weights\n",
       "APA                         Energy  0.0000%\n",
       "BA                      Financials  3.7276%\n",
       "BAX                    Health Care 10.0000%\n",
       "BMY                    Health Care  0.0000%\n",
       "CMCSA       Consumer Discretionary  1.7594%\n",
       "CNP                      Utilities 10.0000%\n",
       "CPB               Consumer Staples  0.0000%\n",
       "DE                     Industrials  9.0767%\n",
       "HPQ         Information Technology  0.0000%\n",
       "JCI         Consumer Discretionary  0.0000%\n",
       "JPM                     Financials  6.2724%\n",
       "LUV                    Industrials  0.0000%\n",
       "MMC                     Financials 10.0000%\n",
       "MO                Consumer Staples  0.0000%\n",
       "MSFT        Information Technology 10.0000%\n",
       "NI                       Utilities 10.0000%\n",
       "PCAR                   Industrials  0.0000%\n",
       "PSA                     Financials  0.0000%\n",
       "SEE                      Materials  0.0000%\n",
       "T      Telecommunications Services  0.0000%\n",
       "TGT         Consumer Discretionary  9.4405%\n",
       "TMO                    Health care  9.7234%\n",
       "TXT                    Industrials  0.0000%\n",
       "VZ     Telecommunications Services 10.0000%\n",
       "ZION                    Financials  0.0000%"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w_classes = pd.concat([asset_classes.set_index('Assets'), w], axis=1)\n",
    "\n",
    "display(w_classes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>weights</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Industry</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Consumer Discretionary</th>\n",
       "      <td>11.1998%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Consumer Staples</th>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Energy</th>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Financials</th>\n",
       "      <td>20.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Health Care</th>\n",
       "      <td>10.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Health care</th>\n",
       "      <td>9.7234%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Industrials</th>\n",
       "      <td>9.0767%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Information Technology</th>\n",
       "      <td>10.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Materials</th>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Telecommunications Services</th>\n",
       "      <td>10.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utilities</th>\n",
       "      <td>20.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             weights\n",
       "Industry                            \n",
       "Consumer Discretionary      11.1998%\n",
       "Consumer Staples             0.0000%\n",
       "Energy                       0.0000%\n",
       "Financials                  20.0000%\n",
       "Health Care                 10.0000%\n",
       "Health care                  9.7234%\n",
       "Industrials                  9.0767%\n",
       "Information Technology      10.0000%\n",
       "Materials                    0.0000%\n",
       "Telecommunications Services 10.0000%\n",
       "Utilities                   20.0000%"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w_classes = w_classes.groupby(['Industry']).sum()\n",
    "\n",
    "display(w_classes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plf.plot_pie(w=w_classes, title='Sharpe Mean Variance', others=0.05, nrow=25,\n",
    "                  cmap = \"tab20\", height=6, width=10, ax=None)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
